A method for generating artificial hyperspectral images can be performed by transforming a new problem into an old one that has already been solved. The problem of how to extract valuable information from co-registered tissue slices can be solved by transforming this problem into an image analysis problem that can be performed with existing techniques. The new problem concerns how to correlate local object-based image analysis results from different tissue slices taken from the same tissue of a given patient. The correlated analysis (co-analysis) results in a much higher quality of the medical evaluation than what a “slide-after-slide analysis” could provide.
A method is sought for extracting valuable information from many high resolution images of adjacent tissue slices that reduces the computing resources required to analyze the large amount of information associated with any particular x-y position in co-registered images.